The field of stochastic optimization studies decision making under uncertainty, when only probabilistic information about the future is available. Finding approximate solutions to...
Leo Harrington surprisingly constructed a machine which can learn any computable function f according to the following criterion (called Bc∗ -identification). His machine, on t...
stract This panel addresses a very important area that is often neglected or overlooked by database systems, database applications developers and data warehouse designers, namely s...
Planning in large, partially observable domains is challenging, especially when a long-horizon lookahead is necessary to obtain a good policy. Traditional POMDP planners that plan...
Discrete event simulations often require a future event list structure to manage events according to their timestamp. The choice of an efficient data structure is vital to the per...